Data Scientist

Company:
Location: Tanjong Pagar

*** Mention DataYoshi when applying ***

What we do

Coda Payments ( https://www.codapayments.com/ ) helps game developers and publishers like Riot Games, Tencent, Garena, EA, KING, Moonton, and other leading digital content providers to monetize their products in places where credit and debit cards aren’t widely used. We establish partnerships with a wide range of alternative payment channel operators who make it possible for customers to pay in other ways: paying cash at retail, using a mobile wallet, making a bank transfer, or redeeming a prepaid card.

Coda also allows publishers to accept payments through these various methods on their own website or at our gaming e-commerce site - codashop.com .

Working at Coda

Life at Coda is fast-paced, challenging, and fun. As a rapidly growing global company, we’re always looking to step up and adapt to changes quickly; there is never a dull day at Coda.

We make things happen in the most impactful and effective manner. If you are always eager to initiate new ideas, hungry to contribute more, derive satisfaction from team wins rather than individual ones, and value integrity, you will fit perfectly into the Coda team!

In Coda Payments we process millions of transactions and collect hundreds of gigabytes of data daily. We are looking for individuals who are willing to join our small, fast-paced, dynamic and growing team to build up data science and data engineering capabilities for Coda.

Responsibilities:

  • Apply machine learning algorithms to design and implement fraud detection algorithms
  • Apply statistical modelling techniques to perform marketing attribution modelling & pricing optimizations
  • Apply natural language processing techniques on text data to derive insights from customer support tickets
  • Support back-end engineers and develop a large scale data warehouse
  • Design and implement ETL processes
  • Implement Direct Acyclic Graphs (DAGs) in Apache Airflow to programmatically author, schedule and monitor workflows
  • Work with data engineers and productionize machine learning algorithms
  • Work with business stakeholders on reporting and BI deliverables

Requirements:

  • PhD in Mathematics/Statistics/Computer Science/Engineering with 3 years of work experience or a Strong Bachelor’s/Masters in one of the above fields with 7 years of work experience.

Must Have:

  • Proficient in programming with Python
  • Proficient in writing and optimizing SQL statements
  • Proficient in supervised and unsupervised machine learning algorithms
  • Proficient in statistical modelling techniques
  • Good communication and presentation skills

Good to Have:

  • Experience in anomaly detection methods
  • Experience in dimensionality reduction techniques
  • Experience in sentiment analysis, keyword extraction methods
  • Experience in productionizing models and/or proficiency in writing performance-optimized code

Nice to Have:

  • Prior experience of working with both streaming and batch data
  • Knowledge of learning to rank algorithms will be an advantage
  • Knowledge of Apache Airflow will be an advantage
  • Knowledge of managed services in Google Cloud Platform or AWS
  • Prior experience of working in cross-functional teams will be an advantage

We are an equal opportunity employer and do not discriminate based on gender, race, age, religion, disability, or other local protected class. We are committed to cultivating an inclusive environment for all employees, and we welcome the diversity that you will bring!

If you are looking for a rapid-growth environment and great teams to work with, you should apply now.

We are sorry to inform you that only shortlisted candidates will be notified as we may be overwhelmed by the number of applicants coming into our system; hence if you do not get a reply from us - don’t give up on us just yet!

We encourage you also to check out our career site at https://jobs.lever.co/codapayments - we may have other suitable openings for you.

*** Mention DataYoshi when applying ***

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